Overview

Dataset statistics

Number of variables13
Number of observations3940
Missing cells95
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory400.3 KiB
Average record size in memory104.0 B

Variable types

Text10
Numeric3

Alerts

YouTube Trailer has 47 (1.2%) missing valuesMissing
IMDB ID has unique valuesUnique
Runtime has 193 (4.9%) zerosZeros

Reproduction

Analysis started2024-01-28 11:50:02.311242
Analysis finished2024-01-28 11:50:05.432328
Duration3.12 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

Title
Text

Distinct3927
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size30.9 KiB
2024-01-28T17:20:05.615292image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length83
Median length55
Mean length15.477411
Min length1

Characters and Unicode

Total characters60981
Distinct characters82
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3914 ?
Unique (%)99.3%

Sample

1st rowPatton Oswalt: Annihilation
2nd rowNew York Doll
3rd rowMickey's Magical Christmas: Snowed in at the House of Mouse
4th rowMickey's House of Villains
5th rowAnd Then I Go
ValueCountFrequency (%)
the 1200
 
11.0%
of 365
 
3.3%
a 158
 
1.4%
in 110
 
1.0%
and 102
 
0.9%
2 81
 
0.7%
to 79
 
0.7%
77
 
0.7%
man 65
 
0.6%
i 52
 
0.5%
Other values (4140) 8668
79.1%
2024-01-28T17:20:06.006651image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7017
 
11.5%
e 6212
 
10.2%
a 3783
 
6.2%
o 3650
 
6.0%
n 3418
 
5.6%
r 3248
 
5.3%
i 3209
 
5.3%
t 3013
 
4.9%
s 2342
 
3.8%
h 2312
 
3.8%
Other values (72) 22777
37.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 42960
70.4%
Uppercase Letter 9659
 
15.8%
Space Separator 7017
 
11.5%
Other Punctuation 840
 
1.4%
Decimal Number 429
 
0.7%
Dash Punctuation 73
 
0.1%
Math Symbol 2
 
< 0.1%
Currency Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6212
14.5%
a 3783
 
8.8%
o 3650
 
8.5%
n 3418
 
8.0%
r 3248
 
7.6%
i 3209
 
7.5%
t 3013
 
7.0%
s 2342
 
5.5%
h 2312
 
5.4%
l 2081
 
4.8%
Other values (21) 9692
22.6%
Uppercase Letter
ValueCountFrequency (%)
T 1332
13.8%
S 842
 
8.7%
M 662
 
6.9%
B 659
 
6.8%
A 543
 
5.6%
D 532
 
5.5%
C 527
 
5.5%
L 450
 
4.7%
W 425
 
4.4%
H 413
 
4.3%
Other values (16) 3274
33.9%
Other Punctuation
ValueCountFrequency (%)
: 412
49.0%
' 158
 
18.8%
. 99
 
11.8%
& 60
 
7.1%
, 51
 
6.1%
! 34
 
4.0%
/ 12
 
1.4%
? 11
 
1.3%
# 1
 
0.1%
* 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 129
30.1%
3 72
16.8%
1 66
15.4%
0 46
 
10.7%
4 27
 
6.3%
9 26
 
6.1%
5 20
 
4.7%
7 17
 
4.0%
8 13
 
3.0%
6 13
 
3.0%
Space Separator
ValueCountFrequency (%)
7017
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 52619
86.3%
Common 8362
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6212
 
11.8%
a 3783
 
7.2%
o 3650
 
6.9%
n 3418
 
6.5%
r 3248
 
6.2%
i 3209
 
6.1%
t 3013
 
5.7%
s 2342
 
4.5%
h 2312
 
4.4%
l 2081
 
4.0%
Other values (47) 19351
36.8%
Common
ValueCountFrequency (%)
7017
83.9%
: 412
 
4.9%
' 158
 
1.9%
2 129
 
1.5%
. 99
 
1.2%
- 73
 
0.9%
3 72
 
0.9%
1 66
 
0.8%
& 60
 
0.7%
, 51
 
0.6%
Other values (15) 225
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60972
> 99.9%
None 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7017
 
11.5%
e 6212
 
10.2%
a 3783
 
6.2%
o 3650
 
6.0%
n 3418
 
5.6%
r 3248
 
5.3%
i 3209
 
5.3%
t 3013
 
4.9%
s 2342
 
3.8%
h 2312
 
3.8%
Other values (66) 22768
37.3%
None
ValueCountFrequency (%)
é 4
44.4%
ä 1
 
11.1%
ô 1
 
11.1%
û 1
 
11.1%
ß 1
 
11.1%
· 1
 
11.1%

Year
Real number (ℝ)

Distinct19
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.1327
Minimum2000
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2024-01-28T17:20:06.118593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2002
Q12009
median2013
Q32016
95-th percentile2018
Maximum2018
Range18
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.821189
Coefficient of variation (CV)0.0023960591
Kurtosis-0.24720024
Mean2012.1327
Median Absolute Deviation (MAD)3
Skewness-0.86509346
Sum7927803
Variance23.243863
MonotonicityNot monotonic
2024-01-28T17:20:06.217801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2017 551
14.0%
2016 457
11.6%
2014 384
9.7%
2015 346
 
8.8%
2013 333
 
8.5%
2018 231
 
5.9%
2012 226
 
5.7%
2011 224
 
5.7%
2010 163
 
4.1%
2009 137
 
3.5%
Other values (9) 888
22.5%
ValueCountFrequency (%)
2000 69
1.8%
2001 82
2.1%
2002 77
2.0%
2003 78
2.0%
2004 100
2.5%
2005 109
2.8%
2006 122
3.1%
2007 123
3.1%
2008 128
3.2%
2009 137
3.5%
ValueCountFrequency (%)
2018 231
5.9%
2017 551
14.0%
2016 457
11.6%
2015 346
8.8%
2014 384
9.7%
2013 333
8.5%
2012 226
5.7%
2011 224
5.7%
2010 163
 
4.1%
2009 137
 
3.5%
Distinct3935
Distinct (%)100.0%
Missing5
Missing (%)0.1%
Memory size30.9 KiB
2024-01-28T17:20:06.461738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1564
Median length727
Mean length507.68895
Min length18

Characters and Unicode

Total characters1997756
Distinct characters108
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3935 ?
Unique (%)100.0%

Sample

1st rowPatton Oswald, despite a personal tragedy, produces his best standup yet. Focusing on the tribulations of the Trump era and life after the loss of a loved one, Patton Oswald continues his journey to contribute joy to the world.
2nd rowA recovering alcoholic and recently converted Mormon, Arthur "Killer" Kane, of the rock band The New York Dolls, is given a chance at reuniting with his band after 30 years.
3rd rowAfter everyone is snowed in at the House of Mouse, Mickey suggests they throw their own Christmas party. Everyone is happy, except for Donald who just isn't in to the Christmas spirit. So Mickey shows a series of cartoons that show just what Christmas is all about. It features a star studded cast of Disney characters from everyone's favorite animated Disney movies.
4th rowThe villains from the popular animated Disney films are gathered at the House of Mouse with plans to take over. Soon, the villains take over the house and kick out Mickey, Donald and Goofy. It's all up to Mickey and his friends to overthrow evil and return the House of Mouse to normal--or as close to normal as it get's.
5th rowIn the cruel world of junior high, Edwin suffers in a state of anxiety and alienation alongside his only friend, Flake. Misunderstood by their families and demoralized at school daily, their fury simmers quietly until an idea for vengeance offers them a terrifying release. Based on the acclaimed novel "Project X" by Jim Shepard, this unflinching look at adolescence explores how the powerful bonds of childhood friendship and search for belonging can become a matter of life or death.
ValueCountFrequency (%)
the 19509
 
5.7%
a 12073
 
3.5%
and 11131
 
3.3%
to 10782
 
3.1%
of 8948
 
2.6%
in 6246
 
1.8%
his 5476
 
1.6%
is 5209
 
1.5%
with 3499
 
1.0%
he 3349
 
1.0%
Other values (27924) 256251
74.8%
2024-01-28T17:20:06.905360image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
338538
16.9%
e 193699
 
9.7%
t 132850
 
6.6%
a 128600
 
6.4%
i 116785
 
5.8%
n 115446
 
5.8%
o 113226
 
5.7%
s 106078
 
5.3%
r 101459
 
5.1%
h 87423
 
4.4%
Other values (98) 563652
28.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1546757
77.4%
Space Separator 338538
 
16.9%
Uppercase Letter 54834
 
2.7%
Other Punctuation 45246
 
2.3%
Decimal Number 4886
 
0.2%
Dash Punctuation 4726
 
0.2%
Open Punctuation 1356
 
0.1%
Close Punctuation 1353
 
0.1%
Currency Symbol 43
 
< 0.1%
Other Symbol 8
 
< 0.1%
Other values (3) 9
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 193699
12.5%
t 132850
 
8.6%
a 128600
 
8.3%
i 116785
 
7.6%
n 115446
 
7.5%
o 113226
 
7.3%
s 106078
 
6.9%
r 101459
 
6.6%
h 87423
 
5.7%
l 66726
 
4.3%
Other values (34) 384465
24.9%
Uppercase Letter
ValueCountFrequency (%)
A 5479
 
10.0%
T 4568
 
8.3%
S 4275
 
7.8%
B 3617
 
6.6%
M 3454
 
6.3%
C 3374
 
6.2%
H 2898
 
5.3%
W 2883
 
5.3%
D 2405
 
4.4%
I 2332
 
4.3%
Other values (18) 19549
35.7%
Other Punctuation
ValueCountFrequency (%)
, 20244
44.7%
. 16827
37.2%
' 5245
 
11.6%
" 1317
 
2.9%
: 518
 
1.1%
? 506
 
1.1%
; 373
 
0.8%
! 101
 
0.2%
/ 57
 
0.1%
& 36
 
0.1%
Other values (4) 22
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 1113
22.8%
0 971
19.9%
9 674
13.8%
2 522
10.7%
5 294
 
6.0%
3 280
 
5.7%
8 277
 
5.7%
4 255
 
5.2%
7 254
 
5.2%
6 246
 
5.0%
Open Punctuation
ValueCountFrequency (%)
( 1355
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1352
99.9%
] 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
= 3
50.0%
+ 3
50.0%
Space Separator
ValueCountFrequency (%)
338538
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4726
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 43
100.0%
Other Symbol
ValueCountFrequency (%)
® 8
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 2
100.0%
Other Number
ValueCountFrequency (%)
¹ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1601591
80.2%
Common 396165
 
19.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 193699
12.1%
t 132850
 
8.3%
a 128600
 
8.0%
i 116785
 
7.3%
n 115446
 
7.2%
o 113226
 
7.1%
s 106078
 
6.6%
r 101459
 
6.3%
h 87423
 
5.5%
l 66726
 
4.2%
Other values (62) 439299
27.4%
Common
ValueCountFrequency (%)
338538
85.5%
, 20244
 
5.1%
. 16827
 
4.2%
' 5245
 
1.3%
- 4726
 
1.2%
( 1355
 
0.3%
) 1352
 
0.3%
" 1317
 
0.3%
1 1113
 
0.3%
0 971
 
0.2%
Other values (26) 4477
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1997582
> 99.9%
None 174
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
338538
16.9%
e 193699
 
9.7%
t 132850
 
6.7%
a 128600
 
6.4%
i 116785
 
5.8%
n 115446
 
5.8%
o 113226
 
5.7%
s 106078
 
5.3%
r 101459
 
5.1%
h 87423
 
4.4%
Other values (76) 563478
28.2%
None
ValueCountFrequency (%)
é 90
51.7%
í 11
 
6.3%
è 10
 
5.7%
á 9
 
5.2%
® 8
 
4.6%
ó 8
 
4.6%
ö 5
 
2.9%
ñ 5
 
2.9%
ô 4
 
2.3%
ë 3
 
1.7%
Other values (12) 21
 
12.1%
Distinct3938
Distinct (%)> 99.9%
Missing1
Missing (%)< 0.1%
Memory size30.9 KiB
2024-01-28T17:20:07.143541image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length831
Median length253
Mean length159.54202
Min length12

Characters and Unicode

Total characters628436
Distinct characters94
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3937 ?
Unique (%)99.9%

Sample

1st rowPatton Oswalt, despite a personal tragedy, produces his best standup yet. Focusing on the tribulations of the Trump era and life after the loss of a loved one, Oswalt continues his journey to contribute joy to the world.
2nd rowA recovering alcoholic and recently converted Mormon, Arthur &quot;Killer&quot; Kane, of the rock band The New York Dolls, is given a chance at reuniting with his band after 30 years.
3rd rowMickey and all his friends hold their own Christmas party at the House of Mouse, after being snowed in.
4th rowThe villains from the popular animated Disney films are gathered at the House of Mouse with plans to take over. Soon, the villains take over the house and kick out Mickey, Donald and Goofy....
5th rowIn the cruel world of junior high, Edwin suffers in a state of anxiety and alienation alongside his only friend, Flake. Misunderstood by their families and demoralized at school daily, ...
ValueCountFrequency (%)
a 6156
 
5.7%
the 5368
 
5.0%
to 3357
 
3.1%
of 3295
 
3.1%
and 2792
 
2.6%
in 2168
 
2.0%
his 1790
 
1.7%
is 1170
 
1.1%
an 1154
 
1.1%
with 1093
 
1.0%
Other values (14125) 78849
73.6%
2024-01-28T17:20:07.493350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
103251
16.4%
e 60271
 
9.6%
t 41564
 
6.6%
a 40910
 
6.5%
o 37306
 
5.9%
i 37025
 
5.9%
n 36843
 
5.9%
r 34914
 
5.6%
s 33175
 
5.3%
h 24864
 
4.0%
Other values (84) 178313
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 492500
78.4%
Space Separator 103253
 
16.4%
Uppercase Letter 15707
 
2.5%
Other Punctuation 12790
 
2.0%
Decimal Number 2207
 
0.4%
Dash Punctuation 1715
 
0.3%
Open Punctuation 127
 
< 0.1%
Close Punctuation 125
 
< 0.1%
Currency Symbol 9
 
< 0.1%
Final Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 60271
12.2%
t 41564
 
8.4%
a 40910
 
8.3%
o 37306
 
7.6%
i 37025
 
7.5%
n 36843
 
7.5%
r 34914
 
7.1%
s 33175
 
6.7%
h 24864
 
5.0%
l 20073
 
4.1%
Other values (29) 125555
25.5%
Uppercase Letter
ValueCountFrequency (%)
A 2825
18.0%
T 1286
 
8.2%
S 1145
 
7.3%
C 934
 
5.9%
B 893
 
5.7%
I 820
 
5.2%
W 811
 
5.2%
M 806
 
5.1%
D 564
 
3.6%
H 553
 
3.5%
Other values (16) 5070
32.3%
Other Punctuation
ValueCountFrequency (%)
. 5911
46.2%
, 4841
37.8%
' 1239
 
9.7%
; 317
 
2.5%
& 293
 
2.3%
: 94
 
0.7%
? 41
 
0.3%
" 23
 
0.2%
/ 17
 
0.1%
! 14
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 521
23.6%
0 438
19.8%
9 337
15.3%
2 239
10.8%
8 127
 
5.8%
6 119
 
5.4%
7 117
 
5.3%
5 111
 
5.0%
3 104
 
4.7%
4 94
 
4.3%
Space Separator
ValueCountFrequency (%)
103251
> 99.9%
  2
 
< 0.1%
Currency Symbol
ValueCountFrequency (%)
$ 8
88.9%
£ 1
 
11.1%
Dash Punctuation
ValueCountFrequency (%)
- 1715
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 125
100.0%
Final Punctuation
ValueCountFrequency (%)
» 2
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 508207
80.9%
Common 120229
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 60271
11.9%
t 41564
 
8.2%
a 40910
 
8.0%
o 37306
 
7.3%
i 37025
 
7.3%
n 36843
 
7.2%
r 34914
 
6.9%
s 33175
 
6.5%
h 24864
 
4.9%
l 20073
 
3.9%
Other values (55) 141262
27.8%
Common
ValueCountFrequency (%)
103251
85.9%
. 5911
 
4.9%
, 4841
 
4.0%
- 1715
 
1.4%
' 1239
 
1.0%
1 521
 
0.4%
0 438
 
0.4%
9 337
 
0.3%
; 317
 
0.3%
& 293
 
0.2%
Other values (19) 1366
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 628377
> 99.9%
None 59
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
103251
16.4%
e 60271
 
9.6%
t 41564
 
6.6%
a 40910
 
6.5%
o 37306
 
5.9%
i 37025
 
5.9%
n 36843
 
5.9%
r 34914
 
5.6%
s 33175
 
5.3%
h 24864
 
4.0%
Other values (67) 178254
28.4%
None
ValueCountFrequency (%)
é 32
54.2%
è 4
 
6.8%
á 3
 
5.1%
ä 3
 
5.1%
  2
 
3.4%
» 2
 
3.4%
ô 2
 
3.4%
ö 2
 
3.4%
í 1
 
1.7%
ü 1
 
1.7%
Other values (7) 7
 
11.9%

Genres
Text

Distinct836
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size30.9 KiB
2024-01-28T17:20:07.657884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length45
Median length35
Mean length24.385787
Min length3

Characters and Unicode

Total characters96080
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique434 ?
Unique (%)11.0%

Sample

1st rowUncategorized
2nd rowDocumentary|Music
3rd rowAdventure|Animation|Comedy|Family|Fantasy
4th rowAnimation|Comedy|Family|Fantasy|Horror
5th rowDrama
ValueCountFrequency (%)
drama 116
 
2.9%
action|crime|drama|thriller 106
 
2.7%
action|adventure|animation|comedy|family 106
 
2.7%
action|drama 103
 
2.6%
action|comedy|drama|romance 102
 
2.6%
action|comedy 83
 
2.1%
action|crime|thriller 77
 
2.0%
action|drama|romance 67
 
1.7%
action|comedy|romance 66
 
1.7%
documentary 64
 
1.6%
Other values (826) 3050
77.4%
2024-01-28T17:20:07.952623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
| 9417
 
9.8%
r 8914
 
9.3%
i 7492
 
7.8%
a 7300
 
7.6%
o 6927
 
7.2%
e 6101
 
6.3%
n 5660
 
5.9%
m 5642
 
5.9%
t 5557
 
5.8%
c 4441
 
4.6%
Other values (26) 28629
29.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 72417
75.4%
Uppercase Letter 13802
 
14.4%
Math Symbol 9417
 
9.8%
Dash Punctuation 444
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 8914
12.3%
i 7492
10.3%
a 7300
10.1%
o 6927
9.6%
e 6101
8.4%
n 5660
7.8%
m 5642
7.8%
t 5557
7.7%
c 4441
6.1%
y 3791
 
5.2%
Other values (10) 10592
14.6%
Uppercase Letter
ValueCountFrequency (%)
A 3904
28.3%
D 2373
17.2%
C 1885
13.7%
F 1260
 
9.1%
T 1172
 
8.5%
H 693
 
5.0%
R 680
 
4.9%
M 650
 
4.7%
S 611
 
4.4%
B 365
 
2.6%
Other values (4) 209
 
1.5%
Math Symbol
ValueCountFrequency (%)
| 9417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 444
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 86219
89.7%
Common 9861
 
10.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 8914
 
10.3%
i 7492
 
8.7%
a 7300
 
8.5%
o 6927
 
8.0%
e 6101
 
7.1%
n 5660
 
6.6%
m 5642
 
6.5%
t 5557
 
6.4%
c 4441
 
5.2%
A 3904
 
4.5%
Other values (24) 24281
28.2%
Common
ValueCountFrequency (%)
| 9417
95.5%
- 444
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96080
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
| 9417
 
9.8%
r 8914
 
9.3%
i 7492
 
7.8%
a 7300
 
7.6%
o 6927
 
7.2%
e 6101
 
6.3%
n 5660
 
5.9%
m 5642
 
5.9%
t 5557
 
5.8%
c 4441
 
4.6%
Other values (26) 28629
29.8%

IMDB ID
Text

UNIQUE 

Distinct3940
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size30.9 KiB
2024-01-28T17:20:08.167323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters35460
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3940 ?
Unique (%)100.0%

Sample

1st rowtt7026230
2nd rowtt0436629
3rd rowtt0300195
4th rowtt0329374
5th rowtt2018111
ValueCountFrequency (%)
tt7026230 1
 
< 0.1%
tt0841046 1
 
< 0.1%
tt6413410 1
 
< 0.1%
tt0300195 1
 
< 0.1%
tt0329374 1
 
< 0.1%
tt2018111 1
 
< 0.1%
tt0208185 1
 
< 0.1%
tt5117670 1
 
< 0.1%
tt0996605 1
 
< 0.1%
tt7614404 1
 
< 0.1%
Other values (3930) 3930
99.7%
2024-01-28T17:20:08.486417image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 7880
22.2%
0 3501
9.9%
2 3334
9.4%
1 3213
9.1%
4 2920
 
8.2%
3 2859
 
8.1%
6 2622
 
7.4%
8 2460
 
6.9%
5 2362
 
6.7%
7 2255
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27580
77.8%
Lowercase Letter 7880
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3501
12.7%
2 3334
12.1%
1 3213
11.6%
4 2920
10.6%
3 2859
10.4%
6 2622
9.5%
8 2460
8.9%
5 2362
8.6%
7 2255
8.2%
9 2054
7.4%
Lowercase Letter
ValueCountFrequency (%)
t 7880
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27580
77.8%
Latin 7880
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3501
12.7%
2 3334
12.1%
1 3213
11.6%
4 2920
10.6%
3 2859
10.4%
6 2622
9.5%
8 2460
8.9%
5 2362
8.6%
7 2255
8.2%
9 2054
7.4%
Latin
ValueCountFrequency (%)
t 7880
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 7880
22.2%
0 3501
9.9%
2 3334
9.4%
1 3213
9.1%
4 2920
 
8.2%
3 2859
 
8.1%
6 2622
 
7.4%
8 2460
 
6.9%
5 2362
 
6.7%
7 2255
 
6.4%

Runtime
Real number (ℝ)

ZEROS 

Distinct145
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.35355
Minimum0
Maximum338
Zeros193
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2024-01-28T17:20:08.629076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.4
Q191
median102
Q3115
95-th percentile139
Maximum338
Range338
Interquartile range (IQR)24

Descriptive statistics

Standard deviation29.798215
Coefficient of variation (CV)0.29693234
Kurtosis5.5394072
Mean100.35355
Median Absolute Deviation (MAD)11
Skewness-1.3886772
Sum395393
Variance887.93361
MonotonicityNot monotonic
2024-01-28T17:20:08.755440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 193
 
4.9%
90 154
 
3.9%
92 106
 
2.7%
100 104
 
2.6%
97 104
 
2.6%
95 99
 
2.5%
98 97
 
2.5%
105 96
 
2.4%
101 95
 
2.4%
107 95
 
2.4%
Other values (135) 2797
71.0%
ValueCountFrequency (%)
0 193
4.9%
3 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
20 1
 
< 0.1%
22 1
 
< 0.1%
26 2
 
0.1%
27 2
 
0.1%
30 2
 
0.1%
ValueCountFrequency (%)
338 1
 
< 0.1%
226 1
 
< 0.1%
219 1
 
< 0.1%
201 1
 
< 0.1%
190 1
 
< 0.1%
187 1
 
< 0.1%
184 1
 
< 0.1%
183 1
 
< 0.1%
180 7
0.2%
179 1
 
< 0.1%

YouTube Trailer
Text

MISSING 

Distinct3883
Distinct (%)99.7%
Missing47
Missing (%)1.2%
Memory size30.9 KiB
2024-01-28T17:20:08.928902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length20
Median length11
Mean length11.003339
Min length11

Characters and Unicode

Total characters42836
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3880 ?
Unique (%)99.7%

Sample

1st row4hZi5QaMBFc
2nd rowjwD04NsnLLg
3rd rowuCKwHHftrU4
4th rowJA03ciYt-Ek
5th row8CdIiD6-iF0
ValueCountFrequency (%)
uky3scpimd8 9
 
0.2%
gdlxpv5nsa4 2
 
0.1%
c95ulpfzhxk 2
 
0.1%
lti0vfcpzns 1
 
< 0.1%
1m5cj4umsce 1
 
< 0.1%
oboyytto5sg 1
 
< 0.1%
4yzjtnj8y3u 1
 
< 0.1%
dwrkl2bjtgq 1
 
< 0.1%
ca6buyvkqoe 1
 
< 0.1%
uckwhhftru4 1
 
< 0.1%
Other values (3873) 3873
99.5%
2024-01-28T17:20:09.244940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 895
 
2.1%
Y 890
 
2.1%
U 883
 
2.1%
E 866
 
2.0%
c 866
 
2.0%
I 865
 
2.0%
g 863
 
2.0%
k 861
 
2.0%
8 859
 
2.0%
4 848
 
2.0%
Other values (57) 34140
79.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 17618
41.1%
Lowercase Letter 17157
40.1%
Decimal Number 6774
 
15.8%
Dash Punctuation 686
 
1.6%
Connector Punctuation 596
 
1.4%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 895
 
5.1%
Y 890
 
5.1%
U 883
 
5.0%
E 866
 
4.9%
I 865
 
4.9%
Q 829
 
4.7%
A 826
 
4.7%
C 633
 
3.6%
S 631
 
3.6%
J 622
 
3.5%
Other values (16) 9678
54.9%
Lowercase Letter
ValueCountFrequency (%)
c 866
 
5.0%
g 863
 
5.0%
k 861
 
5.0%
s 847
 
4.9%
o 824
 
4.8%
w 813
 
4.7%
e 654
 
3.8%
x 636
 
3.7%
t 635
 
3.7%
h 626
 
3.6%
Other values (16) 9532
55.6%
Decimal Number
ValueCountFrequency (%)
8 859
12.7%
4 848
12.5%
0 842
12.4%
1 618
9.1%
6 617
9.1%
5 616
9.1%
3 611
9.0%
7 601
8.9%
9 588
8.7%
2 574
8.5%
Other Punctuation
ValueCountFrequency (%)
/ 2
40.0%
. 2
40.0%
: 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 686
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 596
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34775
81.2%
Common 8061
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 895
 
2.6%
Y 890
 
2.6%
U 883
 
2.5%
E 866
 
2.5%
c 866
 
2.5%
I 865
 
2.5%
g 863
 
2.5%
k 861
 
2.5%
s 847
 
2.4%
Q 829
 
2.4%
Other values (42) 26110
75.1%
Common
ValueCountFrequency (%)
8 859
10.7%
4 848
10.5%
0 842
10.4%
- 686
8.5%
1 618
7.7%
6 617
7.7%
5 616
7.6%
3 611
7.6%
7 601
7.5%
_ 596
7.4%
Other values (5) 1167
14.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 895
 
2.1%
Y 890
 
2.1%
U 883
 
2.1%
E 866
 
2.0%
c 866
 
2.0%
I 865
 
2.0%
g 863
 
2.0%
k 861
 
2.0%
8 859
 
2.0%
4 848
 
2.0%
Other values (57) 34140
79.7%

Rating
Real number (ℝ)

Distinct72
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5556853
Minimum1.7
Maximum9.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2024-01-28T17:20:09.364165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile5.1
Q16.1
median6.6
Q37.1
95-th percentile7.9
Maximum9.5
Range7.8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.89257219
Coefficient of variation (CV)0.13615239
Kurtosis2.1733308
Mean6.5556853
Median Absolute Deviation (MAD)0.5
Skewness-0.77581929
Sum25829.4
Variance0.79668511
MonotonicityNot monotonic
2024-01-28T17:20:09.490369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.2 224
 
5.7%
6.4 209
 
5.3%
6.3 208
 
5.3%
6.7 203
 
5.2%
6.5 202
 
5.1%
6.6 198
 
5.0%
7.1 191
 
4.8%
6.1 190
 
4.8%
6.8 177
 
4.5%
6 157
 
4.0%
Other values (62) 1981
50.3%
ValueCountFrequency (%)
1.7 2
0.1%
2 1
 
< 0.1%
2.2 1
 
< 0.1%
2.3 1
 
< 0.1%
2.4 2
0.1%
2.5 3
0.1%
2.6 1
 
< 0.1%
2.7 2
0.1%
2.8 2
0.1%
2.9 1
 
< 0.1%
ValueCountFrequency (%)
9.5 1
 
< 0.1%
9 1
 
< 0.1%
8.9 1
 
< 0.1%
8.8 3
 
0.1%
8.7 5
 
0.1%
8.6 5
 
0.1%
8.5 11
0.3%
8.4 11
0.3%
8.3 15
0.4%
8.2 22
0.6%
Distinct3932
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size30.9 KiB
2024-01-28T17:20:09.665423image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length150
Median length121
Mean length83.288832
Min length69

Characters and Unicode

Total characters328158
Distinct characters72
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3924 ?
Unique (%)99.6%

Sample

1st rowhttps://hydramovies.com/wp-content/uploads/2018/04/Patton-Oswalt-Annihilation-Movie-Poster.jpg
2nd rowhttps://hydramovies.com/wp-content/uploads/2018/04/New-York-Doll-Movie-Poster.jpg
3rd rowhttps://hydramovies.com/wp-content/uploads/2018/04/Mickeys-Magical-Christmas-Snowed-in-at-the-House-of-Mouse-Movie-Poster.jpg
4th rowhttps://hydramovies.com/wp-content/uploads/2018/04/Mickeys-House-of-Villains-Movie-Poster.jpg
5th rowhttps://hydramovies.com/wp-content/uploads/2018/04/And-Then-I-Go-Movie-Poster.jpg
ValueCountFrequency (%)
https://hydramovies.com/wp-content/uploads/2018/05/extinction-movie-poster.jpg 2
 
0.1%
https://hydramovies.com/wp-content/uploads/2018/04/the-outsider-movie-poster.jpg 2
 
0.1%
https://hydramovies.com/wp-content/uploads/2018/04/restless-movie-poster.jpg 2
 
0.1%
https://hydramovies.com/wp-content/uploads/2018/04/gold-movie-poster.jpg 2
 
0.1%
https://hydramovies.com/wp-content/uploads/2018/04/youth-movie-poster.jpg 2
 
0.1%
https://hydramovies.com/wp-content/uploads/2018/04/the-colony-movie-poster.jpg 2
 
0.1%
https://hydramovies.com/wp-content/uploads/2018/04/gifted-movie-poster.jpg 2
 
0.1%
https://hydramovies.com/wp-content/uploads/2018/04/beyond-the-edge-movie-poster.jpg 2
 
0.1%
https://hydramovies.com/wp-content/uploads/2018/04/love-songs-movie-poster.jpg 1
 
< 0.1%
https://hydramovies.com/wp-content/uploads/2018/04/the-secret-rules-of-modern-living-algorithms-movie-poster.jpg 1
 
< 0.1%
Other values (3922) 3922
99.5%
2024-01-28T17:20:10.029966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 27580
 
8.4%
o 27290
 
8.3%
t 22713
 
6.9%
e 21972
 
6.7%
- 18863
 
5.7%
s 18102
 
5.5%
p 16323
 
5.0%
a 11663
 
3.6%
n 11298
 
3.4%
r 11128
 
3.4%
Other values (62) 141226
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 228140
69.5%
Other Punctuation 39500
 
12.0%
Decimal Number 24116
 
7.3%
Dash Punctuation 18863
 
5.7%
Uppercase Letter 17539
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 27290
12.0%
t 22713
 
10.0%
e 21972
 
9.6%
s 18102
 
7.9%
p 16323
 
7.2%
a 11663
 
5.1%
n 11298
 
5.0%
r 11128
 
4.9%
i 11089
 
4.9%
h 10192
 
4.5%
Other values (21) 66370
29.1%
Uppercase Letter
ValueCountFrequency (%)
M 4602
26.2%
P 4318
24.6%
T 1332
 
7.6%
S 842
 
4.8%
B 659
 
3.8%
A 543
 
3.1%
D 532
 
3.0%
C 527
 
3.0%
L 450
 
2.6%
W 425
 
2.4%
Other values (16) 3309
18.9%
Decimal Number
ValueCountFrequency (%)
0 7926
32.9%
8 4096
17.0%
2 4088
17.0%
1 4034
16.7%
4 2836
 
11.8%
5 600
 
2.5%
6 178
 
0.7%
7 168
 
0.7%
9 118
 
0.5%
3 72
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 27580
69.8%
. 7979
 
20.2%
: 3940
 
10.0%
· 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 18863
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 245679
74.9%
Common 82479
 
25.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 27290
 
11.1%
t 22713
 
9.2%
e 21972
 
8.9%
s 18102
 
7.4%
p 16323
 
6.6%
a 11663
 
4.7%
n 11298
 
4.6%
r 11128
 
4.5%
i 11089
 
4.5%
h 10192
 
4.1%
Other values (47) 83909
34.2%
Common
ValueCountFrequency (%)
/ 27580
33.4%
- 18863
22.9%
. 7979
 
9.7%
0 7926
 
9.6%
8 4096
 
5.0%
2 4088
 
5.0%
1 4034
 
4.9%
: 3940
 
4.8%
4 2836
 
3.4%
5 600
 
0.7%
Other values (5) 537
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 328149
> 99.9%
None 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 27580
 
8.4%
o 27290
 
8.3%
t 22713
 
6.9%
e 21972
 
6.7%
- 18863
 
5.7%
s 18102
 
5.5%
p 16323
 
5.0%
a 11663
 
3.6%
n 11298
 
3.4%
r 11128
 
3.4%
Other values (56) 141217
43.0%
None
ValueCountFrequency (%)
é 4
44.4%
ß 1
 
11.1%
û 1
 
11.1%
ô 1
 
11.1%
ä 1
 
11.1%
· 1
 
11.1%
Distinct2403
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size30.9 KiB
2024-01-28T17:20:10.311299image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length141
Median length104
Mean length13.317259
Min length2

Characters and Unicode

Total characters52470
Distinct characters79
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1688 ?
Unique (%)42.8%

Sample

1st rowBobcat Goldthwait
2nd rowGreg Whiteley
3rd rowTony Craig
4th rowJamie Mitchell
5th rowVincent Grashaw
ValueCountFrequency (%)
david 128
 
1.5%
john 92
 
1.1%
michael 85
 
1.0%
james 68
 
0.8%
peter 60
 
0.7%
scott 59
 
0.7%
paul 56
 
0.7%
robert 48
 
0.6%
steven 46
 
0.6%
mark 39
 
0.5%
Other values (3167) 7614
91.8%
2024-01-28T17:20:10.693104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4844
 
9.2%
a 4482
 
8.5%
4355
 
8.3%
n 3749
 
7.1%
r 3416
 
6.5%
i 3103
 
5.9%
o 3093
 
5.9%
l 2335
 
4.5%
t 1937
 
3.7%
s 1830
 
3.5%
Other values (69) 19326
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39417
75.1%
Uppercase Letter 8379
 
16.0%
Space Separator 4355
 
8.3%
Other Punctuation 234
 
0.4%
Dash Punctuation 85
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4844
12.3%
a 4482
11.4%
n 3749
9.5%
r 3416
 
8.7%
i 3103
 
7.9%
o 3093
 
7.8%
l 2335
 
5.9%
t 1937
 
4.9%
s 1830
 
4.6%
h 1544
 
3.9%
Other values (33) 9084
23.0%
Uppercase Letter
ValueCountFrequency (%)
S 795
 
9.5%
M 742
 
8.9%
J 738
 
8.8%
C 559
 
6.7%
B 540
 
6.4%
A 522
 
6.2%
R 516
 
6.2%
D 511
 
6.1%
G 425
 
5.1%
L 409
 
4.9%
Other values (21) 2622
31.3%
Other Punctuation
ValueCountFrequency (%)
. 208
88.9%
' 24
 
10.3%
? 2
 
0.9%
Space Separator
ValueCountFrequency (%)
4355
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 47796
91.1%
Common 4674
 
8.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4844
 
10.1%
a 4482
 
9.4%
n 3749
 
7.8%
r 3416
 
7.1%
i 3103
 
6.5%
o 3093
 
6.5%
l 2335
 
4.9%
t 1937
 
4.1%
s 1830
 
3.8%
h 1544
 
3.2%
Other values (64) 17463
36.5%
Common
ValueCountFrequency (%)
4355
93.2%
. 208
 
4.5%
- 85
 
1.8%
' 24
 
0.5%
? 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52309
99.7%
None 161
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4844
 
9.3%
a 4482
 
8.6%
4355
 
8.3%
n 3749
 
7.2%
r 3416
 
6.5%
i 3103
 
5.9%
o 3093
 
5.9%
l 2335
 
4.5%
t 1937
 
3.7%
s 1830
 
3.5%
Other values (47) 19165
36.6%
None
ValueCountFrequency (%)
é 34
21.1%
á 28
17.4%
ö 18
11.2%
ó 15
9.3%
ô 10
 
6.2%
í 9
 
5.6%
å 9
 
5.6%
ç 7
 
4.3%
è 6
 
3.7%
ñ 5
 
3.1%
Other values (12) 20
12.4%
Distinct2883
Distinct (%)73.5%
Missing18
Missing (%)0.5%
Memory size30.9 KiB
2024-01-28T17:20:10.928692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length32
Median length26
Mean length13.164457
Min length2

Characters and Unicode

Total characters51631
Distinct characters77
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2303 ?
Unique (%)58.7%

Sample

1st rowPatton Oswalt
2nd rowArthur Kane
3rd rowThomas Hart
4th rowThomas Hart
5th rowBrett Haley
ValueCountFrequency (%)
david 110
 
1.3%
michael 103
 
1.3%
john 91
 
1.1%
james 61
 
0.7%
paul 59
 
0.7%
mark 56
 
0.7%
peter 52
 
0.6%
scott 50
 
0.6%
robert 48
 
0.6%
jonathan 43
 
0.5%
Other values (3456) 7543
91.8%
2024-01-28T17:20:11.275264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4634
 
9.0%
a 4531
 
8.8%
4294
 
8.3%
n 3765
 
7.3%
r 3306
 
6.4%
o 3075
 
6.0%
i 3044
 
5.9%
l 2397
 
4.6%
t 1853
 
3.6%
s 1759
 
3.4%
Other values (67) 18973
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38595
74.8%
Uppercase Letter 8409
 
16.3%
Space Separator 4294
 
8.3%
Other Punctuation 263
 
0.5%
Dash Punctuation 69
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4634
12.0%
a 4531
11.7%
n 3765
9.8%
r 3306
 
8.6%
o 3075
 
8.0%
i 3044
 
7.9%
l 2397
 
6.2%
t 1853
 
4.8%
s 1759
 
4.6%
h 1604
 
4.2%
Other values (31) 8627
22.4%
Uppercase Letter
ValueCountFrequency (%)
J 768
 
9.1%
M 745
 
8.9%
S 697
 
8.3%
B 649
 
7.7%
C 624
 
7.4%
A 554
 
6.6%
D 503
 
6.0%
R 436
 
5.2%
L 421
 
5.0%
G 419
 
5.0%
Other values (21) 2593
30.8%
Other Punctuation
ValueCountFrequency (%)
. 234
89.0%
' 29
 
11.0%
Space Separator
ValueCountFrequency (%)
4294
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Math Symbol
ValueCountFrequency (%)
| 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 47004
91.0%
Common 4627
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4634
 
9.9%
a 4531
 
9.6%
n 3765
 
8.0%
r 3306
 
7.0%
o 3075
 
6.5%
i 3044
 
6.5%
l 2397
 
5.1%
t 1853
 
3.9%
s 1759
 
3.7%
h 1604
 
3.4%
Other values (62) 17036
36.2%
Common
ValueCountFrequency (%)
4294
92.8%
. 234
 
5.1%
- 69
 
1.5%
' 29
 
0.6%
| 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51554
99.9%
None 77
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4634
 
9.0%
a 4531
 
8.8%
4294
 
8.3%
n 3765
 
7.3%
r 3306
 
6.4%
o 3075
 
6.0%
i 3044
 
5.9%
l 2397
 
4.6%
t 1853
 
3.6%
s 1759
 
3.4%
Other values (47) 18896
36.7%
None
ValueCountFrequency (%)
é 17
22.1%
á 16
20.8%
ó 10
13.0%
ô 8
10.4%
í 4
 
5.2%
ñ 3
 
3.9%
Ö 2
 
2.6%
Ó 2
 
2.6%
ü 2
 
2.6%
Á 2
 
2.6%
Other values (10) 11
14.3%

Cast
Text

Distinct3826
Distinct (%)97.7%
Missing24
Missing (%)0.6%
Memory size30.9 KiB
2024-01-28T17:20:11.512095image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length63
Median length51
Mean length35.199949
Min length5

Characters and Unicode

Total characters137843
Distinct characters85
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3758 ?
Unique (%)96.0%

Sample

1st rowPatton Oswalt
2nd rowSylvain Sylvain
3rd rowCarlos Alazraqui|Wayne Allwine
4th rowTony Anselmo|Wayne Allwine
5th rowArman Darbo|Sawyer Barth
ValueCountFrequency (%)
ben 73
 
0.5%
chris 68
 
0.5%
adam 60
 
0.4%
david 58
 
0.4%
james 56
 
0.4%
jason 53
 
0.4%
john 51
 
0.4%
daniel 49
 
0.3%
de 45
 
0.3%
aaron 40
 
0.3%
Other values (8961) 13964
96.2%
2024-01-28T17:20:11.883020image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 12195
 
8.8%
a 12150
 
8.8%
10601
 
7.7%
n 9883
 
7.2%
i 8209
 
6.0%
r 7752
 
5.6%
o 7430
 
5.4%
l 6752
 
4.9%
| 6145
 
4.5%
s 4801
 
3.5%
Other values (75) 51925
37.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 99456
72.2%
Uppercase Letter 21183
 
15.4%
Space Separator 10601
 
7.7%
Math Symbol 6145
 
4.5%
Other Punctuation 250
 
0.2%
Dash Punctuation 208
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 12195
12.3%
a 12150
12.2%
n 9883
9.9%
i 8209
 
8.3%
r 7752
 
7.8%
o 7430
 
7.5%
l 6752
 
6.8%
s 4801
 
4.8%
t 4751
 
4.8%
h 3850
 
3.9%
Other values (38) 21683
21.8%
Uppercase Letter
ValueCountFrequency (%)
J 1856
 
8.8%
M 1842
 
8.7%
C 1688
 
8.0%
S 1651
 
7.8%
B 1563
 
7.4%
A 1336
 
6.3%
R 1259
 
5.9%
D 1195
 
5.6%
H 986
 
4.7%
K 932
 
4.4%
Other values (20) 6875
32.5%
Other Punctuation
ValueCountFrequency (%)
. 176
70.4%
' 72
28.8%
& 1
 
0.4%
; 1
 
0.4%
Space Separator
ValueCountFrequency (%)
10601
100.0%
Math Symbol
ValueCountFrequency (%)
| 6145
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 120639
87.5%
Common 17204
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 12195
 
10.1%
a 12150
 
10.1%
n 9883
 
8.2%
i 8209
 
6.8%
r 7752
 
6.4%
o 7430
 
6.2%
l 6752
 
5.6%
s 4801
 
4.0%
t 4751
 
3.9%
h 3850
 
3.2%
Other values (68) 42866
35.5%
Common
ValueCountFrequency (%)
10601
61.6%
| 6145
35.7%
- 208
 
1.2%
. 176
 
1.0%
' 72
 
0.4%
& 1
 
< 0.1%
; 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 137553
99.8%
None 290
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 12195
 
8.9%
a 12150
 
8.8%
10601
 
7.7%
n 9883
 
7.2%
i 8209
 
6.0%
r 7752
 
5.6%
o 7430
 
5.4%
l 6752
 
4.9%
| 6145
 
4.5%
s 4801
 
3.5%
Other values (49) 51635
37.5%
None
ValueCountFrequency (%)
é 91
31.4%
í 27
 
9.3%
ô 26
 
9.0%
á 22
 
7.6%
ë 16
 
5.5%
ñ 14
 
4.8%
ü 13
 
4.5%
å 12
 
4.1%
è 10
 
3.4%
û 9
 
3.1%
Other values (16) 50
17.2%

Interactions

2024-01-28T17:20:04.567020image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-28T17:20:03.939734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-28T17:20:04.266710image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-28T17:20:04.671395image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-28T17:20:04.049151image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-28T17:20:04.373657image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-28T17:20:04.752106image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-28T17:20:04.143547image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-28T17:20:04.451773image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-01-28T17:20:11.975802image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
RatingRuntimeYear
Rating1.0000.294-0.249
Runtime0.2941.000-0.128
Year-0.249-0.1281.000

Missing values

2024-01-28T17:20:04.928483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:20:05.148744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-01-28T17:20:05.348441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

TitleYearSummaryShort SummaryGenresIMDB IDRuntimeYouTube TrailerRatingMovie PosterDirectorWritersCast
0Patton Oswalt: Annihilation2017Patton Oswald, despite a personal tragedy, produces his best standup yet. Focusing on the tribulations of the Trump era and life after the loss of a loved one, Patton Oswald continues his journey to contribute joy to the world.Patton Oswalt, despite a personal tragedy, produces his best standup yet. Focusing on the tribulations of the Trump era and life after the loss of a loved one, Oswalt continues his journey to contribute joy to the world.Uncategorizedtt7026230664hZi5QaMBFc7.4https://hydramovies.com/wp-content/uploads/2018/04/Patton-Oswalt-Annihilation-Movie-Poster.jpgBobcat GoldthwaitPatton OswaltPatton Oswalt
1New York Doll2005A recovering alcoholic and recently converted Mormon, Arthur "Killer" Kane, of the rock band The New York Dolls, is given a chance at reuniting with his band after 30 years.A recovering alcoholic and recently converted Mormon, Arthur &quot;Killer&quot; Kane, of the rock band The New York Dolls, is given a chance at reuniting with his band after 30 years.Documentary|Musictt043662975jwD04NsnLLg7.9https://hydramovies.com/wp-content/uploads/2018/04/New-York-Doll-Movie-Poster.jpgGreg WhiteleyArthur KaneSylvain Sylvain
2Mickey's Magical Christmas: Snowed in at the House of Mouse2001After everyone is snowed in at the House of Mouse, Mickey suggests they throw their own Christmas party. Everyone is happy, except for Donald who just isn't in to the Christmas spirit. So Mickey shows a series of cartoons that show just what Christmas is all about. It features a star studded cast of Disney characters from everyone's favorite animated Disney movies.Mickey and all his friends hold their own Christmas party at the House of Mouse, after being snowed in.Adventure|Animation|Comedy|Family|Fantasytt030019565uCKwHHftrU46.8https://hydramovies.com/wp-content/uploads/2018/04/Mickeys-Magical-Christmas-Snowed-in-at-the-House-of-Mouse-Movie-Poster.jpgTony CraigThomas HartCarlos Alazraqui|Wayne Allwine
3Mickey's House of Villains2001The villains from the popular animated Disney films are gathered at the House of Mouse with plans to take over. Soon, the villains take over the house and kick out Mickey, Donald and Goofy. It's all up to Mickey and his friends to overthrow evil and return the House of Mouse to normal--or as close to normal as it get's.The villains from the popular animated Disney films are gathered at the House of Mouse with plans to take over. Soon, the villains take over the house and kick out Mickey, Donald and Goofy....Animation|Comedy|Family|Fantasy|Horrortt03293740JA03ciYt-Ek6.6https://hydramovies.com/wp-content/uploads/2018/04/Mickeys-House-of-Villains-Movie-Poster.jpgJamie MitchellThomas HartTony Anselmo|Wayne Allwine
4And Then I Go2017In the cruel world of junior high, Edwin suffers in a state of anxiety and alienation alongside his only friend, Flake. Misunderstood by their families and demoralized at school daily, their fury simmers quietly until an idea for vengeance offers them a terrifying release. Based on the acclaimed novel "Project X" by Jim Shepard, this unflinching look at adolescence explores how the powerful bonds of childhood friendship and search for belonging can become a matter of life or death.In the cruel world of junior high, Edwin suffers in a state of anxiety and alienation alongside his only friend, Flake. Misunderstood by their families and demoralized at school daily, ...Dramatt2018111998CdIiD6-iF07.6https://hydramovies.com/wp-content/uploads/2018/04/And-Then-I-Go-Movie-Poster.jpgVincent GrashawBrett HaleyArman Darbo|Sawyer Barth
5An Extremely Goofy Movie2000It's a big time in Max's life. He's college bound with his friends and finally free of his embarrassing father as he strives to be a top contender for the X-Games. Unfortunately, Goofy loses his job and learns that he cannot get another job without a college degree. To his son's mortification, Goofy decides to join him in his campus to get that degree. Desperate to distract his father, Max talks him into joining the competing Gamma Fraternity team and introduces him to a wonderful librarian who shares his nostalgic love for 1970's pastimes. Unfortunately, things do not go according to plan as events put this father-son relationship to the test.Max goes to college, but to his embarassment his father loses his job and goes to his son's campus.Animation|Comedy|Family|Sporttt020818579H8oSvldAGfg6.4https://hydramovies.com/wp-content/uploads/2018/04/An-Extremely-Goofy-Movie-Movie-Poster.jpgDouglas McCarthyScott Spencer GordenBill Farmer|Jason Marsden|Jeff Bennett
6Peter Rabbit2018Based on the books by Beatrix Potter: Peter Rabbit (James Corden;) his three sisters: Flopsy (Margot Robbie,) Mopsy (Elizabeth Debicki) and Cotton Tail (Daisy Ridley) and their cousin Benjamin (Colin Moody) enjoy their days harassing Mr McGregor in his vegetable garden. Until one day he dies and no one can stop them roaming across his house and lands for a full day or so. However, when one of Mr McGregor's relatives inherits the house and goes to check it out, he finds much more than he bargained for. What ensues, is a battle of wills between the new Mr McGregor and the rabbits. But when he starts to fall in love with Bea (Rose Byrne,) a real lover of all nature, his feelings towards them begin to change. But is it too late?Feature adaptation of Beatrix Potter's classic tale of a rebellious rabbit trying to sneak into a farmer's vegetable garden.Adventure|Animation|Comedy|Family|Fantasytt5117670957Pa_Weidt086.6https://hydramovies.com/wp-content/uploads/2018/04/Peter-Rabbit-Movie-Poster.jpgWill GluckRob LieberFayssal Bazzi|James Corden
7Love Songs2007Julie's boyfriend Ismaël lives with her; rather than worry about the time he spends with his colleague Alice, Julie invites Alice to join them. The three walk the streets of Paris, party, read, and sleep together. Sometimes it's lighthearted, sometimes there are jealousies. Then death strikes. In various ways, those left come to terms with the departure and absence of a loved one: showing concern, eating together, attempting new relationships, trying to "be there" for the other. Then, the spirit returns and new commitments are possible. The romantic elements of musical comedy play in contrast to the ambivalence of the lyrics and the story.A musical interpretation of three lovers living in Paris.Uncategorizedtt099660591s54vpKAFmS07.2https://hydramovies.com/wp-content/uploads/2018/04/Love-Songs-Movie-Poster.jpgChristophe HonoréChristophe HonoréClotilde Hesme|Louis Garrel|Ludivine Sagnier
889201789 tells the incredible story of one of football's greatest triumphs: when against all odds Arsenal snatched the Championship title from Liverpool at Anfield in the last minute of the last game of the 1988/89 season. It's a universal tale of a band of brothers who, led by a charismatic and deeply respected manager, came together to defy the odds and create history. Mixing archive and previously unseen footage with revealing interviews, insights and memories from the original squad, game officials, famous fans and the people who were there on the night this is the definitive account of a watershed moment in football and a must-watch for any sports fan.The true story of a sporting miracle, when Arsenal went to Anfield on the last day of the 1988/89 season needing to beat the best team in England by two clear goals to snatch the title.Uncategorizedtt7614404915hfAExhHTMM8.1https://hydramovies.com/wp-content/uploads/2018/04/89-Movie-Poster.jpgDave StewartLee DixonIan Wright
9The Foster Boy2011The illegitimate orphan child, 12-year-old Max, is sold by the local minister for a basket of food to the Bösiger family, who own a mountain farm. Max' initial hope of finally finding a loving home is brutally shattered: The farmer and his wife treat Max like livestock, and their son Jacob humiliates and abuses him. Only the local teacher notices the child suffering on the farm.A Swiss-German rural peasant family takes Max, a crude 15-year-old boy, into a foster situation of constant bullying. Soon, a foster girl is added to the mix.Dramatt2057931107E9Qv_XVJ-js7.4https://hydramovies.com/wp-content/uploads/2018/04/The-Foster-Boy-Movie-Poster.jpgMarkus ImbodenPlinio BachmannKatja Riemann|Maximilian Simonischek|Stefan Kurt
TitleYearSummaryShort SummaryGenresIMDB IDRuntimeYouTube TrailerRatingMovie PosterDirectorWritersCast
3930The Child in Time2017Children's author Stephen Lewis is shopping with 4-year old daughter Kate when she suddenly disappears. Failure to find her puts a strain on his marriage, his wife Julie leaving to live in a seaside village, though Stephen regularly visits her. Stephen continues to write but is asked by the prime minister to check on his best friend Charles Dark, who has resigned his cabinet membership to live in an isolated woodland retreat with his wife Thelma. Stephen is perturbed by Charles' apparent regression to childhood, reminding him of his own loss and, returning to London, erroneously believes that another little girl is Kate. Three years after the disappearance Thelma asks Stephen, still keeping Kate's room for her, for help with the increasingly disturbed Charles, leading to a shocking discovery though a later phone call from Julie provides a new beginning for them both.The life of a children's book author is turned upside down when his daughter goes missing.Dramatt654007882DuPXdnSWoLk6.1https://hydramovies.com/wp-content/uploads/2018/09/The-Child-in-Time-Movie-Poster.jpgJulian FarinoIan McEwanBenedict Cumberbatch|Kelly Macdonald|Stephen Campbell Moore
3931Mr. Magorium's Wonder Emporium2007Molly Mahoney is the manager of Mr. Magorium's Wonder Emporium, the awesome toy store owned by Mr. Edward Magorium. Molly was a promising composer and piano player when she was a girl, and now she is a twenty-three year-old insecure woman who feels stuck in her job. Among the costumers of the Emporium is the lonely hat collector, Eric Applebaum, who has only Molly and Mr. Magorium for friends. When the last pair of shoes that Mr. Magorium bought in Toscana is worn, he hires the accountant, Henry Weston to adjust the accounts of the Emporium. Furthermore, he claims that he is two hundred and forty-three years old and his time to go has come; he gives a block of wood called Congreve cube to Molly and asks Henry to transfer the Emporium to her name. Molly tries to convince Mr. Magorium to stay in his magical toy store instead of "going".Molly Mahoney is the awkward and insecure manager of Mr. Magorium's Wonder Emporium, the strangest, most fantastic, most wonderful toy store in the world. But when Mr. Magorium, the 243-year-old eccentric who owns the store, bequeaths the store to her, a dark and ominous change begins to take over the once-remarkable Emporium.Comedy|Family|Fantasytt045741993m4Mrga2aSL06.2https://hydramovies.com/wp-content/uploads/2018/09/Mr.-Magoriums-Wonder-Emporium-Movie-Poster.jpgZach HelmZach HelmDustin Hoffman|Jason Bateman|Natalie Portman
3932High Fantasy2017A group of young friends on a camping trip, deep in the South African countryside wake up to discover they have all swapped bodies. Their individual cultural heritage and experience of these strange happenings couldn't be more different; and stranded in the wilderness, they will have to navigate a personal-political labyrinth if their friendship and their lives are ever to be the same again. The stage is set for comedy to turn to tragedy, for the fantasy of South Africa's "Rainbow Nation" to become a painful awakening.A group of young friends on a camping trip, deep in the South African countryside wake up to discover they have all swapped bodies.Comedy|Dramatt728406671MdPl_FdYbWM5.4https://hydramovies.com/wp-content/uploads/2018/09/High-Fantasy-Movie-Poster.jpgJenna Cato BassLiza ScholtzFrancesca Varrie Michel|Nala Khumalo|Qondiswa James
3933Curve2015Mallory Rutledge is driving her fiancé's truck to Denver to meet him and get married. While driving in the lonely road, she talks to her sister Ella and decides to take a detour to visit the Grand Canyon. Out of the blue, the truck stops and Mallory can get no service in her cell phone. However the gentle drifter Christian Laughton offers to fix the car and Mallory accepts. Then she offers a ride to him and when she is driving, he says pornography to her. She asks him to leave but he shows a knife and tells her to go to a derelict motel. Mallory sees that the psychopath Christian is not wearing the seat bell and decides to throw the truck off the road in a curve. But the leg of Mallory is trapped in the overturned car and Christian leaves her without any help, in the beginning of Mallory's worst nightmare. Will she escape from the vehicle and from the psychopath?A young woman becomes trapped in her car after a hitchhiker causes her to have an automobile accident.Horror|Thrillertt321290481lPlunQ3rzV45.4https://hydramovies.com/wp-content/uploads/2018/09/Curve-Movie-Poster.jpgIain SoftleyKimberly Lofstrom JohnsonJulianne Hough|Penelope Mitchell|Teddy Sears
3934Office Uprising2018An employee at a weapons factory discovers that an energy drink turns his co-workers into zombiesAn employee at a weapons factory discovers that an energy drink turns his co-workers into zombiesAction|Comedy|Horrortt625102492IfKhTnK_IBA6.9https://hydramovies.com/wp-content/uploads/2018/09/Office-Uprising-Movie-Poster.jpgLin OedingPeter Gamble RobinsonBrenton Thwaites|Jane Levy|Karan Soni
3935Skyscraper2018FBI Hostage Rescue Team leader and U.S. war veteran Will Sawyer now assesses security for skyscrapers. On assignment in Hong Kong he finds the tallest, safest building in the world suddenly ablaze and he's been framed for it. A wanted man on the run, Will must find those responsible, clear his name and somehow rescue his family who are trapped inside the building - above the fire line.A security expert must infiltrate a burning skyscraper, 225 stories above ground, when his family are trapped inside by criminals.Action|Thrillertt5758778102t9QePUT-Yt86.0https://hydramovies.com/wp-content/uploads/2018/09/Skyscraper-Movie-Poster.jpgRawson Marshall ThurberRawson Marshall ThurberChin Han|Dwayne Johnson|Neve Campbell
3936Trench 112017In the final days of WWI, an allied army unit led by a shell-shocked soldier is sent to investigate a mysterious abandoned German facility located deep underground. What they find is fate worse than death.In the final days of WWI, an allied army unit led by a shell-shocked soldier is sent to investigate a mysterious abandoned German facility located deep underground.Horror|Thriller|Wartt503329090bVDGukfxFAk5.3https://hydramovies.com/wp-content/uploads/2018/09/Trench-11-Movie-Poster.jpgLeo SchermanMatt BooiCharlie Carrick|Robert Stadlober|Rossif Sutherland
3937My Daddy's in Heaven2017Becca, Adam and their 5-year-old daughter Acie are a perfect family until a tragic accident during a 4th of July celebration kills their father. Struggling with grief, Becky decides she needs to leave the family farm and all its memories. She leaves Acie with her grandfather Ben and visits with her friend from school, June. With all the best intent, June offers Becky plenty of distraction from her family life. Fueled by her anger at G*d and loss of faith, Becky starts drinking and making other self-destructive choices. Then, after Becky is arrested, Ben threatens to keep Acie until Becky is back on track. A chance encounter in a bus station with a traveler gives Becky what she needs to restore her faith and reunite with her family.Becca, Adam and their 5-year-old daughter Acie are a perfect family until a tragic accident during a 4th of July celebration kills their father. Struggling with grief, Becky decides she needs to leave the family farm and all its memories.Comedy|Drama|Familytt646027692bv0Eh2VhTTA5.8https://hydramovies.com/wp-content/uploads/2018/09/My-Daddys-in-Heaven-Movie-Poster.jpgWaymon BooneJoseph NasserCorbin Bernsen|Jenn Gotzon Chandler|Lee Benton
3938Keeping Up with the Steins2006In toney Brentwood, Benjamin Fiedler prepares for his bar mitzvah; trouble is, he understands neither its meaning nor the Hebrew, and his parents (particularly his successful-agent father) are planning the most lavish party possible. Benjamin wants his dad to give him some space, so he gets an idea: to invite his grandfather, who left the family years ago and for whom Benjamin's dad has an intense dislike, to come two weeks early. Thanks in part to grandpa - and to the immediate family's love - Benjamin may have a shot at figuring out what it means to be a man.A 13-year-old boy uses his upcoming bar mitzvah to reconcile the strained relationship between his father and grandfather.Comedytt0415949908TKLR1_JVLU5.4https://hydramovies.com/wp-content/uploads/2018/09/Keeping-Up-with-the-Steins-Movie-Poster.jpgScott MarshallMark ZakarinDaryl Sabara|Garry Marshall|Jeremy Piven
3939UFO2018Derek (Alex Sharp) a brilliant college student, haunted by a childhood UFO sighting, believes that mysterious sightings reported at multiple airports across the United States are UFO's. With the help of his girlfriend, Natalie (Ella Purnell), and his advanced mathematics professor, Dr. Hendricks (X-Files' Gillian Anderson), Derek races to unravel the mystery with FBI special agent Franklin Ahls (David Strathairn) on his heels.A college student, who sees a UFO, uses his exceptional math skills to investigate the sighting with his friends while the FBI follows closely behind.Action|Sci-Fi|Thrillertt629079888gxUcHrPhewY6.2https://hydramovies.com/wp-content/uploads/2018/09/UFO-Movie-Poster.jpgRyan EslingerRyan EslingerAlex Sharp|Benjamin Beatty|Ella Purnell